Image segmentation - Specify an area of interest

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Hi guys,
I have two images ('A' and 'B'). On the first image 'A' there are circle-shaped objects e.g. those chips. What I did so far is to identify those objects with their information about coordinates and radii. Here is the toy-code for the first part:
rgb = imread('coloredChips.png');
figure
imshow(rgb)
d = imdistline;
delete(d);
gray_image = rgb2gray(rgb);
imshow(gray_image);
[centers, radii] = imfindcircles(rgb,[20 25],'ObjectPolarity','dark')
[centers, radii] = imfindcircles(rgb,[20 25],'ObjectPolarity','dark', ...
'Sensitivity',0.9)
imshow(rgb);
h = viscircles(centers,radii);
Based on the information about the position and radii in 'A', I want to run a second edge detection algorithm on image 'B' to identify there a circle-shaped object, that lies somewhere within the object of the first picture 'A'. Both images has the same dimension.
Objective: Get the coordinates and radii of the objects in image 'A' and the same for image 'B'.
My thoughts: My idea was to draw rectangles around the main object in 'image' B and make the background black. This is not the best solution but it would reduce the running time.
Do you have any hints for me, how to solve this problem?
Thanks a lot.

采纳的回答

Image Analyst
Image Analyst 2016-11-22
You can use a mask of the circles, determined from A, on B and analyze what is remaining.
% Creates a mask from one image and applies it to an image.
clc; % Clear the command window.
workspace; % Make sure the workspace panel is showing.
clearvars;
close all;
format long g;
format compact;
fontSize = 20;
rgbImage = imread('coloredChips.png');
% Get the dimensions of the image. numberOfColorBands should be = 3.
[rows, columns, numberOfColorChannels] = size(rgbImage);
subplot(3, 2, 1);
imshow(rgbImage)
title('Original RGB Image', 'fontSize', fontSize);
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
% Get rid of tool bar and pulldown menus that are along top of figure.
set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')
% d = imdistline;
% delete(d);
grayImage = rgb2gray(rgbImage);
subplot(3, 2, 2);
imshow(grayImage);
drawnow;
title('Gray Scale Image', 'fontSize', fontSize);
% [centers, radii] = imfindcircles(rgbImage,[20 25],'ObjectPolarity','dark')
[centers, radii] = imfindcircles(rgbImage,[20 25],'ObjectPolarity','dark', ...
'Sensitivity',0.9)
subplot(3, 2, 3);
imshow(rgbImage);
h = viscircles(centers, radii);
title('Original RGB Image with Circles in Overlay', 'fontSize', fontSize);
% Make a binary image mask
subplot(3, 2, 4);
mask = false(rows, columns);
for k = 1 : length(centers)
% Create a logical image of a circle with specified
% diameter, center, and image size.
% First create the image.
[columnsInImage rowsInImage] = meshgrid(1:columns, 1:rows);
% Next create the circle in the image.
centerX = centers(k, 1);
centerY = centers(k, 2);
radius = radii(k);
circlePixels = (rowsInImage - centerY).^2 ...
+ (columnsInImage - centerX).^2 <= radius.^2;
% circlePixels is a 2D "logical" array.
% Now, display it.
imshow(circlePixels) ;
mask(circlePixels) = true;
imshow(mask);
drawnow;
end
imshow(mask);
title('Binary image mask', 'fontSize', fontSize);
% Mask the image using bsxfun() function
maskedRgbImage = bsxfun(@times, rgbImage, cast(mask, 'like', rgbImage));
subplot(3, 2, 5);
imshow(maskedRgbImage);
title('Masked RGB Image', 'fontSize', fontSize);
  6 个评论
Kamu
Kamu 2016-11-28
编辑:Kamu 2016-11-28
I apologise for my unprecise question. Please, let me try again. Let say, we have the masked image of coins (grayscale) like here LINK . I would like to distinguish between those coins based on their stamping and fill only those holes, that have a specific stamping of interests (all coins have the same size).
Image Analyst
Image Analyst 2016-11-28
That's exactly what my "Image Segmentation Tutorial" does. It finds coins.

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